Novel tools for diagnosis, prognosis, and monitoring of central nervous system (CNS) diseases are urgently needed. To place the problem in perspective, just one neurodegenerative disease, Alzheimer?s (AD), is now the sixth-leading cause of death in the United States, places a burden of nearly half a trillion dollars per year on caregivers and taxpayers, and is expected to double in prevalence within the next decade. Reliable and interpretable liquid biopsy tests of easily accessed fluids such as blood would be of high value in the clinic. Extracellular vesicles (EVs) have recently emerged as important players in pathophysiology of CNS diseases. Comprising a diversity of double-leaflet membrane-bound particles, EVs have been reported by several groups including ours to spread proteins implicated in pathogenesis both in vitro and in vivo. Importantly, EVs from the central nervous system can be found in the periphery, appearing to transgress the blood brain barrier quite readily. These EVs may provide a non-invasive window into the health of the CNS and, potentially, specific CNS cell types. Indeed, our collaborator on this application, D. Kapogiannis, has published multiple biomarker findings obtained from AD patient blood using a precipitation/immunoaffinity (PIA) approach to enrich neuronal and astrocytic EVs. Despite this important success, there is now an opportunity to improve on the existing technique, increasing sensitivity, specificity, and throughput while reducing sample size and hands-on time. We plan to address this need, using innovative techniques, tools, and approaches to obtain highly pure antigen-containing populations of CNS-EVs from four main CNS cell types. We hypothesize firstly (Aims 1 and 2, R21 Phase) that novel developments in EV isolation and characterization?1) a multiplexed capture/interferometry instrument (ExoView) of nanoView Diagnostics and 2) a next-generation, multipass-enabled, optically integrated resistive pulse technology from Electronic BioSciences?offer substantial improvements over the current state-of- the-field PIA technique at all steps of the workflow, benchmarked with the guidance of our collaborator and PIA co-developer. Secondly, in the R33 Phase (Aims 3 and 4), we expect to verify and optimize the sensitivity, specificity, limits of detection, and any sample pre-processing steps. Using carefully designed spike-ins and mixtures, along with pure EVs from culture of iPSC-derived cells and cells genomically edited as negative controls, we will confirm the cell of origin of EVs from multiple biological sources. Specific, detailed milestones are offered for each phase, including the transition from the proof-of-principle R21 phase into the more expansive R33 validation phase.